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The aim of the present study was to identify potential biomarkers of hepatocellular carcinoma (HCC). Three gene expression profiles of GSE95698, GSE49515 and GSE76427 and a DNA methylation profile of GSE73003 were downloaded from the Gene Expression Omnibus (GEO) database, each comprising data regarding HCC and control tissue samples. The differentially expressed genes (DEGs) between the HCC group and the control group were identified using the limma software package. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the overlapping DEGs. The PPI network of the overlapping DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins. A total of 41 DEGs were identified in HCC the group compared with control group. The overlapping DEGs were enriched in 11 GO terms and 3 KEGG pathways. A total of 6,349 DMSs were identified, and 6 of the differentially expressed genes were also differentially methylated [Denticleless protein homolog ( DTL ), Dual specificity phosphatase 1 ( DUSP1 ), Eomesodermin, Endothelial cell specific molecule 1, Nuclear factor κ-light-chain gene enhancer of activated B cells inhibitor, α (NFKBIA) and suppressor of cytokine signaling 2 ( SOCS2 )]. The present study suggested that DTL, DUSP1, NFKBIA and SOCS2 may be potential biomarkers of HCC, and the tumor protein 'p53 signaling', 'forkhead box O1' signaling and 'metabolic' pathways may serve roles in the pathogenesis of HCC.

Potential biomarkers of HCC based on gene expression and DNA methylation profiles